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app.py

@@ -1,76 +1,87 @@
-import streamlit as st
-import groq
-import hypernetx as hnx
-import oolama  # Certifique-se de que o módulo oolama esteja disponível
-
-client = groq.Groq()
-
-def build_hypergraph(input_data):
-    try:
-        tokens = oolama.tokenize(input_data)
-        entities = oolama.extract_entities(tokens)
-        relations = oolama.extract_relations(tokens)
-
-        hypergraph = hnx.Hypergraph()
-        for entity in entities:
-            hypergraph.add_node(entity)
-        for relation in relations:
-            hypergraph.add_edge(relation['entities'], relation['type'])
-
-        return hypergraph
-    except Exception as e:
-        st.error(f"Erro ao construir o hipergrafo: {e}")
-        return None
-
-def infer_on_hypergraph(hypergraph):
-    try:
-        oolama_input = hnx.convert_to_oolama_format(hypergraph)
-        results = oolama.infer(oolama_input)
-        return results
-    except Exception as e:
-        st.error(f"Erro ao realizar inferência no hipergrafo: {e}")
-        return None
-
-def format_hypergraph_inference_results(results):
-    try:
-        formatted_results = oolama.format_results(results)
-        return formatted_results
-    except Exception as e:
-        st.error(f"Erro ao formatar os resultados da inferência: {e}")
-        return None
-
-def generate_hypergraph_response(prompt):
-    hypergraph = build_hypergraph(prompt)
-    if hypergraph is None:
-        return "Erro ao gerar hipergrafo."
-
-    results = infer_on_hypergraph(hypergraph)
-    if results is None:
-        return "Erro ao realizar inferência no hipergrafo."
-
-    formatted_results = format_hypergraph_inference_results(results)
-    if formatted_results is None:
-        return "Erro ao formatar os resultados da inferência."
-
-    return formatted_results
-
-def main():
-    st.set_page_config(page_title="g1 prototype", page_icon="🧠", layout="wide")
-
-    st.title("g1: Usando Llama-3.1 70b no Groq com Cadeias de Raciocínio Baseadas em Arquitetura de Hipergrafos")
-
-    st.markdown("""
-    Este é um protótipo inicial que utiliza métodos heurísticos e hermenêuticos com uma arquitetura de hipergrafos para melhorar a precisão das saídas. 
-    """)
-
-    user_query = st.text_input("Insira sua consulta:", placeholder="Por exemplo, Quantos 'R's existem na palavra morango?")
-
-    if user_query:
-        st.write("Gerando resposta com base na arquitetura de hipergrafos...")
-
-        response = generate_hypergraph_response(user_query)
-
-        st.write(response)
-
-if _name_ == "_main_":
-    main()
+"""
+This module provides functionalities for processing input data and generating hypergraphs.
+"""
+
+import streamlit as st
+import groq
+import hypernetx as hnx
+import oolama
+
+def process_input_data(input_data):
+    """
+    Process the input data to extract entities and relations, and create a hypergraph.
+
+    Args:
+        input_data (str): The input data to process.
+
+    Returns:
+        hnx.Hypergraph: The generated hypergraph.
+    """
+    try:
+        tokens = oolama.tokenize(input_data)
+        entities = oolama.extract_entities(tokens)
+        relations = oolama.extract_relations(tokens)
+
+        hypergraph = hnx.Hypergraph()
+        for entity in entities:
+            hypergraph.add_node(entity)
+        for relation in relations:
+            hypergraph.add_edge(relation['entities'], relation['type'])
+
+        return hypergraph
+    except oolama.OolamaError as e:
+        st.error(f"Error processing input data: {e}")
+        return None
+
+def infer_on_hypergraph(hypergraph):
+    """
+    Perform inference on the given hypergraph.
+
+    Args:
+        hypergraph (hnx.Hypergraph): The hypergraph to perform inference on.
+
+    Returns:
+        dict: The inference results.
+    """
+    try:
+        oolama_input = hnx.convert_to_oolama_format(hypergraph)
+        results = oolama.infer(oolama_input)
+        return results
+    except oolama.OolamaError as e:
+        st.error(f"Error during inference: {e}")
+        return None
+
+def format_hypergraph_inference_results(results):
+    """
+    Format the inference results for display.
+
+    Args:
+        results (dict): The inference results to format.
+
+    Returns:
+        str: The formatted results.
+    """
+    try:
+        formatted_results = "\n".join([f"{key}: {value}" for key, value in results.items()])
+        return formatted_results
+    except Exception as e:
+        st.error(f"Error formatting results: {e}")
+        return ""
+
+def main():
+    """
+    Main function to run the Streamlit app.
+    """
+    st.title("Hypergraph Inference App")
+
+    input_data = st.text_area("Enter input data:")
+    if st.button("Process"):
+        hypergraph = process_input_data(input_data)
+        if hypergraph:
+            results = infer_on_hypergraph(hypergraph)
+            if results:
+                formatted_results = format_hypergraph_inference_results(results)
+                st.text_area("Inference Results:", formatted_results)
+
+if __name__ == "__main__":
+    main()